Abstract
Volume data, such as 3D reconstructions from histological sections orMRI and CT data, are commonly used in studies in biology and medicine. The quantification of morphological parameters and changes within a region of interest is a key concern in such studies. Specifically, it is often required to measure the distance between two points. These distance measurements have to follow a track through the tissue when measuring in sheetlike or contorted organs like the developing heart. A tool was developed that enables this kind of distance measurements. Three existing neighborhood estimators were compared; two of Verwer and one of Kiryati, all originally designed to compute chamfer distances in data sets with isotropic, cubic voxels. The estimators were therefore adjusted to handle non-isotropic data sets. Moreover, the shortest path along a track within a given tissue was calculated. The measurement of known distances, through a simplified model of an early heart tube, with anisotropic voxels was used decide which of the three estimators should be implemented. The observed Root Mean Square (RMS) errors were similar to the ones reported in literature in the unrestrained isotropic case. The adjusted Verwer estimator measuring in a 53 neighborhood performed best by far with the lowest mean and RMS errors.
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